diff --git a/python/mxnet/ndarray/numpy/random.py b/python/mxnet/ndarray/numpy/random.py
index 693cca05d9ce..414c28df4364 100644
--- a/python/mxnet/ndarray/numpy/random.py
+++ b/python/mxnet/ndarray/numpy/random.py
@@ -348,8 +348,6 @@ def gamma(shape, scale=1.0, size=None, dtype=None, ctx=None, out=None):
     """
     from ...numpy import ndarray as np_ndarray
     input_type = (isinstance(shape, np_ndarray), isinstance(scale, np_ndarray))
-    if dtype is None:
-        dtype = 'float32'
     if ctx is None:
         ctx = current_context()
     if out is not None:
diff --git a/python/mxnet/symbol/numpy/random.py b/python/mxnet/symbol/numpy/random.py
index 73866ae90bf0..84b8bf4fbc14 100644
--- a/python/mxnet/symbol/numpy/random.py
+++ b/python/mxnet/symbol/numpy/random.py
@@ -320,8 +320,6 @@ def gamma(shape, scale=1.0, size=None, dtype=None, ctx=None, out=None):
     """
     from ._symbol import _Symbol as np_symbol
     input_type = (isinstance(shape, np_symbol), isinstance(scale, np_symbol))
-    if dtype is None:
-        dtype = 'float32'
     if ctx is None:
         ctx = current_context()
     if out is not None:
diff --git a/src/operator/numpy/random/np_gamma_op.cc b/src/operator/numpy/random/np_gamma_op.cc
index 72e337b1642b..210843fc2087 100644
--- a/src/operator/numpy/random/np_gamma_op.cc
+++ b/src/operator/numpy/random/np_gamma_op.cc
@@ -38,7 +38,7 @@ inline bool NumpyGammaOpType(const nnvm::NodeAttrs& attrs,
   if (otype != -1) {
     (*out_attrs)[0] = otype;
   } else {
-    (*out_attrs)[0] = mshadow::kFloat32;
+    (*out_attrs)[0] = GetDefaultDtype(param.dtype);
   }
   return true;
 }
diff --git a/src/operator/numpy/random/np_gamma_op.h b/src/operator/numpy/random/np_gamma_op.h
index 83e8f1f5242b..b4a2c98db6aa 100644
--- a/src/operator/numpy/random/np_gamma_op.h
+++ b/src/operator/numpy/random/np_gamma_op.h
@@ -62,12 +62,14 @@ struct NumpyGammaParam : public dmlc::Parameter<NumpyGammaParam> {
       .describe("Context of output, in format [xpu|xpu|xpu_pinned](n)."
                 " Only used for imperative calls.");
     DMLC_DECLARE_FIELD(dtype)
+      .add_enum("None", -1)
       .add_enum("float32", mshadow::kFloat32)
       .add_enum("float64", mshadow::kFloat64)
       .add_enum("float16", mshadow::kFloat16)
-      .set_default(mshadow::kFloat32)
-      .describe("DType of the output in case this can't be inferred. "
-                "Defaults to float32 if not defined (dtype=None).");
+      .set_default(-1)
+      .describe("DType of the output in case this can't be inferred."
+                "Defaults to float64 or float32 if not defined (dtype=None),"
+                "which depends on your current default dtype.");
   }
 };
 
diff --git a/tests/python/unittest/test_numpy_default_dtype.py b/tests/python/unittest/test_numpy_default_dtype.py
index 68a07e932bfd..760127800bbd 100644
--- a/tests/python/unittest/test_numpy_default_dtype.py
+++ b/tests/python/unittest/test_numpy_default_dtype.py
@@ -56,6 +56,7 @@ def get_workloads(name):
     'hanning',
     'hamming',
     'blackman',
+    'gamma',
     'random.uniform',
     'random.normal',
     'true_divide'
@@ -119,6 +120,10 @@ def _add_dtype_workload_hamming():
     DtypeOpArgMngr.add_workload('hamming', 3)
 
 
+def _add_dtype_workload_gamma():
+    DtypeOpArgMngr.add_workload('gamma', 3)
+
+
 def _add_dtype_workload_blackman():
     DtypeOpArgMngr.add_workload('blackman', 3)
 
@@ -151,6 +156,7 @@ def _prepare_workloads():
     _add_dtype_workload_hanning()
     _add_dtype_workload_hamming()
     _add_dtype_workload_blackman()
+    _add_dtype_workload_gamma()
     _add_dtype_workload_random_uniform()
     _add_dtype_workload_random_normal()
     _add_dtype_workload_true_divide()